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Application of Interpretable Machine Learning Models to Predict the Risk Factors of HBV-Related Liver Cirrhosis in CHB Patients Based on Routine Clinical Data: A Retrospective Cohort Study.

Journal of medical virology
Chronic hepatitis B (CHB) infection represents a significant global public health issue, often leading to hepatitis B virus (HBV)-related liver cirrhosis (HBV-LC) with poor prognoses. Early identification of HBV-LC risk is essential for timely interv...

Text phrase-mining in identifying and classifying maternal proteins and genes across preeclampsia and similar pathologies.

Physiological reports
This study aims to demonstrate that text phrase-mining and natural language processing (NLP) can annotate huge quantities of obstetrics textual data for the discovery and evaluation of maternal protein/gene (MPG)-disease interactions involved in the ...

Research on Prediction model of Carotid-Femoral Pulse Wave Velocity: Based on Machine Learning Algorithm.

Journal of clinical hypertension (Greenwich, Conn.)
Carotid-femoral pulse wave velocity (cf-PWV) is an important but difficult to obtain measure of arterial stiffness and an independent predictor of cardiovascular events and all-cause mortality. The objective of this study was to develop a predictive ...

Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader.

Radiology
Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency...

Understanding artificial intelligence through the eyes of future nurses: Insights from nursing students.

Saudi medical journal
OBJECTIVES: To explore nursing students' perceptions and understanding of artificial intelligence (AI), aiming to identify and address critical knowledge gaps to support effective integration into educational practices.

Exploring Mechanisms and Biomarkers of Breast Cancer Invasion and Migration: An Explainable Gene-Pathway-Compounds Neural Network.

Cancer medicine
BACKGROUNDS: Exploring the molecular features that drive breast cancer invasion and migration remains an important biological and clinical challenge. In recent years, the use of interpretable machine learning models has enhanced our understanding of ...

Deep Learning Radiopathomics Models Based on Contrast-enhanced MRI and Pathologic Imaging for Predicting Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.

Radiology. Imaging cancer
Purpose To develop deep learning (DL) radiopathomics models based on contrast-enhanced MRI and pathologic imaging to predict vessels encapsulating tumor clusters (VETC) and survival in hepatocellular carcinoma (HCC). Materials and Methods In this ret...

[Evaluating the accuracy of large language models in answering mammography screening questions in Italian and English: a study based on the Eusobi guidelines.].

Recenti progressi in medicina
INTRODUCTION: Artificial intelligence (AI) is transforming various aspects of everyday life, including healthcare, through large language models (LLMs) like ChatGPT, Gemini, and Copilot. These systems are increasingly used to disseminate medical info...

The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.

The Journal of the Acoustical Society of America
Vocal intensity is quantified by sound pressure level (SPL). The SPL can be measured by either using a sound level meter or by comparing the energy of the recorded speech signal with the energy of the recorded calibration tone of a known SPL. Neither...